R Under development (unstable) (2024-08-21 r87038 ucrt) -- "Unsuffered Consequences"
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> library(testthat)
>  Sys.setenv('OMP_THREAD_LIMIT'=2)
>  library(rlibkriging)

Attaching package: 'rlibkriging'

The following objects are masked from 'package:base':

    load, save

> 
> ##library(rlibkriging, lib.loc="bindings/R/Rlibs")
> ##library(testthat)
> 
> for (kernel in c("exp","matern3_2","matern5_2","gauss")) {
+   context(paste0("Check LogLikelihood for kernel ",kernel))
+   
+   f = function(x) 1-1/2*(sin(12*x)/(1+x)+2*cos(7*x)*x^5+0.7)
+   plot(f)
+   n <- 5
+   set.seed(123)
+   X <- as.matrix(runif(n))
+   y = f(X)
+   points(X,y)
+ 
+   k = DiceKriging::km(design=X,response=y,covtype = kernel,control = list(trace=F))
+   ll = function(theta) DiceKriging::logLikFun(theta,k)
+   plot(Vectorize(ll),ylab="LL",xlab="theta",xlim=c(0.01,1))
+   for (x in seq(0.01,1,,11)){
+     envx = new.env()
+     llx = DiceKriging::logLikFun(x,k,envx)
+     gllx = DiceKriging::logLikGrad(x,k,envx)
+     arrows(x,llx,x+.1,llx+.1*gllx)
+   }
+   
+   #library(rlibkriging)
+   r <- Kriging(y, X, kernel)
+   ll2 = function(theta) logLikelihoodFun(r,theta)$logLikelihood
+   # plot(Vectorize(ll2),col='red',add=T) # FIXME fails with "error: chol(): decomposition failed"
+   for (x in seq(0.01,1,,11)){
+     envx = new.env()
+     ll2x = logLikelihoodFun(r,x)$logLikelihood
+     gll2x = logLikelihoodFun(r,x,return_grad = T)$logLikelihoodGrad
+     arrows(x,ll2x,x+.1,ll2x+.1*gll2x,col='red')
+   }
+   
+   precision <- 1e-8  # the following tests should work with it, since the computations are analytical
+   x=.5
+   xenv=new.env()
+   test_that(desc="logLik is the same that DiceKriging one", 
+             expect_equal(logLikelihoodFun(r,x)$logLikelihood[1],DiceKriging::logLikFun(x,k,xenv),tolerance = precision))
+   
+   test_that(desc="logLik Grad is the same that DiceKriging one", 
+             expect_equal(logLikelihoodFun(r,x,return_grad=T)$logLikelihoodGrad,DiceKriging::logLikGrad(x,k,xenv),tolerance= precision))
+ }
Test passed 😸
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> 
> 
> ########################## 2D
> 
> for (kernel in c("matern3_2","matern5_2","gauss","exp")) {
+   context(paste0("Check LogLikelihood for kernel ",kernel))
+   
+   f <- function(X) apply(X, 1, function(x) prod(sin((x-.5)^2)))
+   n <- 100
+   set.seed(123)
+   X <- cbind(runif(n),runif(n),runif(n))
+   y <- f(X)
+ 
+   k = DiceKriging::km(design=X,response=y,covtype = kernel,control = list(trace=F))
+   
+   ##library(rlibkriging)
+   r <- Kriging(y, X, kernel)
+   
+   precision <- 1e-8  # the following tests should work with it, since the computations are analytical
+   x=c(.2,.5,.7)
+   xenv=new.env()
+   test_that(desc="logLik is the same that DiceKriging one", 
+             expect_equal(logLikelihoodFun(r,x)$logLikelihood[1],DiceKriging::logLikFun(x,k,xenv),tolerance = precision))
+   
+   test_that(desc="logLik Grad is the same that DiceKriging one", 
+             expect_equal(logLikelihoodFun(r,x,return_grad=T)$logLikelihoodGrad[1,],t(DiceKriging::logLikGrad(x,k,xenv))[1,],tolerance= precision))
+ }
Test passed 🥳
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> 
> proc.time()
   user  system elapsed 
   3.79    0.39    4.20